16,520 research outputs found
Activities of \gamma-ray emitting isotopes in rainwater from Greater Sudbury, Canada following the Fukushima incident
We report the activity measured in rainwater samples collected in the Greater
Sudbury area of eastern Canada on 3, 16, 20, and 26 April 2011. The samples
were gamma-ray counted in a germanium detector and the isotopes 131I and 137Cs,
produced by the fission of 235U, and 134Cs, produced by neutron capture on
133Cs, were observed at elevated levels compared to a reference sample of
ice-water. These elevated activities are ascribed to the accident at the
Fukushima Dai-ichi nuclear reactor complex in Japan that followed the 11 March
earthquake and tsunami. The activity levels observed at no time presented
health concerns.Comment: 4 pages, 8 figure
Analytical Solution of the Voter Model on Disordered Networks
We present a mathematical description of the voter model dynamics on
heterogeneous networks. When the average degree of the graph is
the system reaches complete order exponentially fast. For , a finite
system falls, before it fully orders, in a quasistationary state in which the
average density of active links (links between opposite-state nodes) in
surviving runs is constant and equal to , while an
infinite large system stays ad infinitum in a partially ordered stationary
active state. The mean life time of the quasistationary state is proportional
to the mean time to reach the fully ordered state , which scales as , where is the number of nodes of the
network, and is the second moment of the degree distribution. We find
good agreement between these analytical results and numerical simulations on
random networks with various degree distributions.Comment: 20 pages, 8 figure
Accuracy of Genome-Enabled Prediction in a Dairy Cattle Population using Different Cross-Validation Layouts
The impact of extent of genetic relatedness on accuracy of genome-enabled predictions was assessed using a dairy cattle population and alternative cross-validation (CV) strategies were compared. The CV layouts consisted of training and testing sets obtained from either random allocation of individuals (RAN) or from a kernel-based clustering of individuals using the additive relationship matrix, to obtain two subsets that were as unrelated as possible (UNREL), as well as a layout based on stratification by generation (GEN). The UNREL layout decreased the average genetic relationships between training and testing animals but produced similar accuracies to the RAN design, which were about 15% higher than in the GEN setting. Results indicate that the CV structure can have an important effect on the accuracy of whole-genome predictions. However, the connection between average genetic relationships across training and testing sets and the estimated predictive ability is not straightforward, and may depend also on the kind of relatedness that exists between the two subsets and on the heritability of the trait. For high heritability traits, close relatives such as parents and full-sibs make the greatest contributions to accuracy, which can be compensated by half-sibs or grandsires in the case of lack of close relatives. However, for the low heritability traits the inclusion of close relatives is crucial and including more relatives of various types in the training set tends to lead to greater accuracy. In practice, CV designs should resemble the intended use of the predictive models, e.g., within or between family predictions, or within or across generation predictions, such that estimation of predictive ability is consistent with the actual application to be considered
Cliques and duplication-divergence network growth
A population of complete subgraphs or cliques in a network evolving via
duplication-divergence is considered. We find that a number of cliques of each
size scales linearly with the size of the network. We also derive a clique
population distribution that is in perfect agreement with both the simulation
results and the clique statistic of the protein-protein binding network of the
fruit fly. In addition, we show that such features as fat-tail degree
distribution, various rates of average degree growth and non-averaging,
revealed recently for only the particular case of a completely asymmetric
divergence, are present in a general case of arbitrary divergence.Comment: 7 pages, 6 figure
A Search for Small-Scale Clumpiness in Dense Cores of Molecular Clouds
We have analyzed HCN(1-0) and CS(2-1) line profiles obtained with high
signal-to-noise ratios toward distinct positions in three selected objects in
order to search for small-scale structure in molecular cloud cores associated
with regions of high-mass star formation. In some cases, ripples were detected
in the line profiles, which could be due to the presence of a large number of
unresolved small clumps in the telescope beam. The number of clumps for regions
with linear scales of ~0.2-0.5 pc is determined using an analytical model and
detailed calculations for a clumpy cloud model; this number varies in the
range: ~2 10^4-3 10^5, depending on the source. The clump densities range from
~3 10^5-10^6 cm^{-3}, and the sizes and volume filling factors of the clumps
are ~(1-3) 10^{-3} pc and ~0.03-0.12. The clumps are surrounded by inter-clump
gas with densities not lower than ~(2-7) 10^4 cm^{-3}. The internal thermal
energy of the gas in the model clumps is much higher than their gravitational
energy. Their mean lifetimes can depend on the inter-clump collisional rates,
and vary in the range ~10^4-10^5 yr. These structures are probably connected
with density fluctuations due to turbulence in high-mass star-forming regions.Comment: 23 pages including 4 figures and 4 table
Structure of a large social network
We study a social network consisting of over individuals, with a
degree distribution exhibiting two power scaling regimes separated by a
critical degree , and a power law relation between degree and
local clustering. We introduce a growing random model based on a local
interaction mechanism that reproduces all of the observed scaling features and
their exponents. Our results lend strong support to the idea that several very
different networks are simultenously present in the human social network, and
these need to be taken into account for successful modeling.Comment: 5 pages, 5 figure
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